Neural decoding reveals dynamic patterns of visual chunk memory processes

IF 3.5 3区 医学 Q2 NEUROSCIENCES Brain Research Bulletin Pub Date : 2025-02-01 DOI:10.1016/j.brainresbull.2025.111208
Chantat Leong , Fei Gao , Zhen Yuan
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Abstract

Chunk memory constitutes the basic unit that manages long-term memory and converts it into immediate decision-making processes, it remains unclear how to interpret and organize incoming information to form effective chunk memory. This paper investigates electroencephalography (EEG) patterns from the perspective of time-domain feature extraction using chunk memory in visual statistical learning and combines time-resolved multivariate pattern analysis (MVPA). The GFP and MVPA results revealed that chunk memory processes occurred during specific time windows in the learning phase. These processes included attention modulation (P1), recognition and feature extraction (P2), and segmentation for long-term memory conversion (P6). In the decision-making stage, chunk memory processes were encoded by four ERP components. Scene processing correlated with P1, followed by feature extraction facilitated by P2, encoding process (P4), and segmentation process (P6). This paper identifies the early process of chunk memory through implicit learning and applies univariate and multivariate approaches to establish the neural activity patterns of the early chunk memory process, which provides ideas for subsequent related studies.
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神经解码揭示了视觉块记忆过程的动态模式。
块记忆是管理长期记忆并将其转化为即时决策过程的基本单元,但如何解释和组织传入的信息以形成有效的块记忆尚不清楚。利用视觉统计学习中的块记忆从时域特征提取的角度研究脑电图(EEG)模式,并结合时间分辨多元模式分析(MVPA)。GFP和MVPA结果显示,块记忆过程发生在学习阶段的特定时间窗内。这些过程包括注意调节(P1)、识别和特征提取(P2)以及长时记忆转换的分割(P6)。在决策阶段,块记忆过程由四个ERP组件编码。场景处理与P1相关,其次是P2促进的特征提取、编码过程(P4)和分割过程(P6)。本文通过内隐学习识别块记忆的早期过程,并运用单变量和多变量方法建立块记忆早期过程的神经活动模式,为后续相关研究提供思路。
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来源期刊
Brain Research Bulletin
Brain Research Bulletin 医学-神经科学
CiteScore
6.90
自引率
2.60%
发文量
253
审稿时长
67 days
期刊介绍: The Brain Research Bulletin (BRB) aims to publish novel work that advances our knowledge of molecular and cellular mechanisms that underlie neural network properties associated with behavior, cognition and other brain functions during neurodevelopment and in the adult. Although clinical research is out of the Journal''s scope, the BRB also aims to publish translation research that provides insight into biological mechanisms and processes associated with neurodegeneration mechanisms, neurological diseases and neuropsychiatric disorders. The Journal is especially interested in research using novel methodologies, such as optogenetics, multielectrode array recordings and life imaging in wild-type and genetically-modified animal models, with the goal to advance our understanding of how neurons, glia and networks function in vivo.
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